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Amazon Elastic Inference vs BigML: What are the differences?
Amazon Elastic Inference: GPU-Powered Deep Learning Inference Acceleration. Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon; BigML: Machine Learning, made simple. Predictive analytics for big data and not-so-big data. BigML provides a hosted machine learning platform for advanced analytics. Through BigML's intuitive interface and/or its open API and bindings in several languages, analysts, data scientists and developers alike can quickly build fully actionable predictive models and clusters that can easily be incorporated into related applications and services.
Amazon Elastic Inference and BigML belong to "Machine Learning as a Service" category of the tech stack.
Pros of Amazon Elastic Inference
Pros of BigML
- Ease of use, great REST API and ML workflow automation1